Prevalence and measurement of post-exertional malaise in post-acute COVID-19 syndrome: A systematic review and meta-analysis
Year: 2024
Type: review
Study designs: Systematic Review, Meta-Analysis
Abstract: OBJECTIVE: Post-exertional malaise (PEM) is a common and debilitating symptom of post-acute COVID-19 syndrome (PACS), and it is also included in the core outcome set for PACS. Our aims are to determine the prevalence of PEM in patients with PACS, and to review the measurement tools utilized in studies assessing PEM among these patients. METHODS: A systematic literature search was conducted up to 29 February 2024 across four databases: PubMed, EMBASE, Web of Science, and Cochrane Library. Studies were included if they evaluated PACS individuals who had at least one persistent symptom, with the mean or median follow-up duration of at least 3 months after COVID-19 diagnosis or hospital discharge, and specially reported on PEM or any measurement tools utilized to assess PEM. Data extraction and quality assessment were performed independently by two authors. RESULTS: After screening 953 articles, 12 studies comprising 2665 patients were included in the meta-analysis, and 16 studies were included in the narrative review. The pooled prevalence of PEM among PACS patients at 3 months or more after COVID-19 diagnosis was 0.55 (95 % CI, 0.38, 0.71). Moreover, narrative review identified seven questionnaires used to assess PEM in PACS individuals, with the DePaul Symptom Questionnaire-Post Exertional Malaise (DSQ-PEM) being the most frequently utilized instrument. CONCLUSION: Our findings indicate that over half of the PACS individuals experience PEM, and seven questionnaires have been identified for researchers to assess PEM. It is imperative to develop effective intervention strategies to treat and alleviate the burden of PEM.
Source: General Hospital Psychiatry
Authors: Yi An, Ziyu Guo, Jin Fan, Tingting Luo, Huimin Xu, Huiying Li, Xi Wu
Institution: Chengdu University of Traditional Chinese Medicine
Language: English
Subfield: Neurology
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $3,210
Award: G1723518114
OpenAlex ID: W4403579295
